Roles of big data analytics and organizational culture in developing innovation capabilities: a hybrid PLS‐fsQCA approach

IF 6.7 2区 管理学 Q1 BUSINESS
R&D Management Pub Date : 2024-09-17 DOI:10.1111/radm.12719
Behzad Foroughi, Mohammad Iranmanesh, Nick Hajli, Lee Shih Ling, Morteza Ghobakhloo, Davoud Nikbin
{"title":"Roles of big data analytics and organizational culture in developing innovation capabilities: a hybrid PLS‐fsQCA approach","authors":"Behzad Foroughi, Mohammad Iranmanesh, Nick Hajli, Lee Shih Ling, Morteza Ghobakhloo, Davoud Nikbin","doi":"10.1111/radm.12719","DOIUrl":null,"url":null,"abstract":"Big data analytics creates and consolidates competitive advantage by providing insights on data with enormous variety, velocity, and volume to firms. However, many companies' investments in big data analytics were unsuccessful, and they could not gain full advantage of these technologies. This study investigates the impacts of big data analytics capabilities on innovation quality and speed by considering organizational learning culture as a moderator. The study's data are obtained from a survey of 221 managers in the manufacturing industry. We integrate the Partial Least Squares (PLS) technique and fuzzy‐set Qualitative Comparative Analysis (fsQCA) to perform the analysis. The findings of PLS indicated that big data analytics capabilities positively influence both innovation quality and speed. However, innovation quality influences both market performance and financial performance, and innovation speed only affects market performance. Organizational learning culture negatively moderates the impacts of big data analytics on innovation speed and quality. fsQCA uncovered four solutions with varied combinations of factors that predict the high market and financial performance. The theoretical and practical implications are explained at the end of the paper.","PeriodicalId":21040,"journal":{"name":"R&D Management","volume":"44 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"R&D Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1111/radm.12719","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0

Abstract

Big data analytics creates and consolidates competitive advantage by providing insights on data with enormous variety, velocity, and volume to firms. However, many companies' investments in big data analytics were unsuccessful, and they could not gain full advantage of these technologies. This study investigates the impacts of big data analytics capabilities on innovation quality and speed by considering organizational learning culture as a moderator. The study's data are obtained from a survey of 221 managers in the manufacturing industry. We integrate the Partial Least Squares (PLS) technique and fuzzy‐set Qualitative Comparative Analysis (fsQCA) to perform the analysis. The findings of PLS indicated that big data analytics capabilities positively influence both innovation quality and speed. However, innovation quality influences both market performance and financial performance, and innovation speed only affects market performance. Organizational learning culture negatively moderates the impacts of big data analytics on innovation speed and quality. fsQCA uncovered four solutions with varied combinations of factors that predict the high market and financial performance. The theoretical and practical implications are explained at the end of the paper.
大数据分析和组织文化在发展创新能力中的作用:PLS-fsQCA 混合方法
大数据分析通过为企业提供对种类繁多、速度快、数量大的数据的洞察力来创造和巩固竞争优势。然而,许多公司在大数据分析方面的投资并不成功,无法充分利用这些技术。本研究以组织学习文化为调节因素,探讨大数据分析能力对创新质量和速度的影响。研究数据来自对制造业 221 名管理人员的调查。我们整合了偏最小二乘法(PLS)技术和模糊集定性比较分析法(fsQCA)进行分析。偏最小二乘法的结果表明,大数据分析能力对创新质量和速度都有积极影响。但是,创新质量同时影响市场绩效和财务绩效,而创新速度只影响市场绩效。组织学习文化负向调节了大数据分析对创新速度和质量的影响。本文最后阐述了其理论和实践意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
R&D Management
R&D Management Multiple-
CiteScore
11.30
自引率
9.50%
发文量
0
期刊介绍: R&D Management journal publishes articles which address the interests of both practising managers and academic researchers in research and development and innovation management. Covering the full range of topics in research, development, design and innovation, and related strategic and human resource issues - from exploratory science to commercial exploitation - articles also examine social, economic and environmental implications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信